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The different CCA algorithms were applied on Y and Y t−1 of dimension n×N to allow us to generate canonical correlation components representing maximally correlated temporal profile.
The neural dynamics of interest can be obtained by correlating the modulation profile of the canonical correlation components with the time series representing average neural dynamics for regions of interest (ROIs).
Now, in the tracking mode, all correlation components have to be taken into account, since they gather in one aggregate perturbation called average interference parameter.
Legend: = The correlation was not calculated in cases where at least one of the correlation components had less than 50% of samples with concentrations above the limit of detection (LOD).
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Note that a slow correlation component is often visible when pCF is calculated along the cytoplasm-to-nucleus direction (example shown in Fig. 5C).
Because the latter analysis is confined to one quantitative trait, the environmental correlation component is forced to be zero.
The Pearson's correlation component of this score gives increased weight to those probes for which there is a linear relationship between its correlations with all other probes and their HR p-values.
The inclusion of temporal auto-correlation component improved the accuracy of all models for total phosphorus and total nitrogen.
In Fig. 3g we magnify the auto-correlation component for a situation where we have switched x0 off (auto-correlation only!).
In Fig. 3f a small early auto-correlation component (AC) is followed by a big, cross-correlation dominated hump (AC + CC) as soon as x0 occurs.
Its prediction relies on the secondary correlation with components that can be measured by NIRS (Gillon et al. 1999).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com